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Maritime space understanding using multiple radar systems by iterative image reconstuction algorithm

机译:迭代图像重建算法在多雷达系统中对海洋空间的理解

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Understanding a space where autonomous robots work is an open problem. In case of maritime space, it is also very important. For this purpose, marine radar has been used to acquire images around the maritime vehicles. However, radar images are easily distorted by signal attenuation with distance, blurring due to antenna directivity, reflection by obstructs, etc. There are some conventional methods to improve the image quality. However, there is a limitation due to the acquisition mechanism of radar systems. To overcome the limitation, this study shows a novel approach, which uses multiple radar images to understand the maritime space. The method estimates radar cross section (RCS) from multiple radar images by iterative image reconstruction algorithm. Performance of the proposed method is validated using actual radar images taken by marine radar system equipped on a ship. The experimental results showed that the proposed method presents a maritime space map with high image quality and without distance attenuation, sidelobe diffusion.
机译:了解自主机器人的工作空间是一个悬而未决的问题。对于海洋空间,这也非常重要。为此目的,已经使用了海上雷达来获取海上车辆周围的图像。但是,雷达图像容易因距离的信号衰减而失真,由于天线方向性而引起的模糊,障碍物的反射等。有一些常规方法可以改善图像质量。但是,由于雷达系统的获取机制而存在局限性。为了克服这种局限性,本研究显示了一种新颖的方法,该方法使用多个雷达图像来了解海洋空间。该方法通过迭代图像重建算法从多个雷达图像估计雷达截面(RCS)。所提出的方法的性能通过使用舰载海上雷达系统拍摄的实际雷达图像进行了验证。实验结果表明,所提出的方法可以提供图像质量高,无距离衰减,旁瓣扩散的海洋空间图。

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